What is involved in Prescriptive Analytics
Find out what the related areas are that Prescriptive Analytics connects with, associates with, correlates with or affects, and which require thought, deliberation, analysis, review and discussion. This unique checklist stands out in a sense that it is not per-se designed to give answers, but to engage the reader and lay out a Prescriptive Analytics thinking-frame.
How far is your company on its Prescriptive Analytics journey?
Take this short survey to gauge your organization’s progress toward Prescriptive Analytics leadership. Learn your strongest and weakest areas, and what you can do now to create a strategy that delivers results.
To address the criteria in this checklist for your organization, extensive selected resources are provided for sources of further research and information.
Start the Checklist
Below you will find a quick checklist designed to help you think about which Prescriptive Analytics related domains to cover and 133 essential critical questions to check off in that domain.
The following domains are covered:
Prescriptive Analytics, Applied statistics, Big data, Business analytics, Business intelligence, Business operations, Business process, Computational model, Computational science, Data mining, Decision Engineering, Decision Management, Health, Safety and Environment, Health care in the United States, Health care provider, Map reduce, Mathematical model, Mathematical sciences, Natural gas prices, Operations research, Predictive analytics, Structured data, Unstructured data, Utility companies:
Prescriptive Analytics Critical Criteria:
Infer Prescriptive Analytics results and report on setting up Prescriptive Analytics without losing ground.
– Why is it important to have senior management support for a Prescriptive Analytics project?
– How is the value delivered by Prescriptive Analytics being measured?
– How do we keep improving Prescriptive Analytics?
Applied statistics Critical Criteria:
Powwow over Applied statistics goals and sort Applied statistics activities.
– Does Prescriptive Analytics include applications and information with regulatory compliance significance (or other contractual conditions that must be formally complied with) in a new or unique manner for which no approved security requirements, templates or design models exist?
– Is Supporting Prescriptive Analytics documentation required?
– What are the Essentials of Internal Prescriptive Analytics Management?
Big data Critical Criteria:
Judge Big data management and frame using storytelling to create more compelling Big data projects.
– What are the particular research needs of your organization on big data analytics that you find essential to adequately handle your data assets?
– Does your organization perceive the need for more effort to promote security and trust in data technologies?
– Is the software compatible with new database formats for raw, unstructured, and semi-structured big data?
– How should we organize to capture the benefit of Big Data and move swiftly to higher maturity stages?
– Future: Given the focus on Big Data where should the Chief Executive for these initiatives report?
– Quality vs. Quantity: What data are required to satisfy the given value proposition?
– What are the ways in which cloud computing and big data can work together?
– What is the Quality of the Result if the Quality of the Data/Metadata is poor?
– What would be needed to support collaboration on data sharing in your sector?
– Can good algorithms, models, heuristics overcome Data Quality problems?
– Hybrid partitioning (across rows/terms and columns/documents) useful?
– Does your organization have the necessary skills to handle big data?
– What if the data cannot fit on your computer?
– Overall cost (matrix, weighting, SVD, sims)?
– How can we summarize streaming data?
– What are some impacts of Big Data?
– What is collecting all this data?
– Who is collecting all this data?
– Is Big data different?
– What s limiting the task?
Business analytics Critical Criteria:
Drive Business analytics issues and remodel and develop an effective Business analytics strategy.
– Will new equipment/products be required to facilitate Prescriptive Analytics delivery for example is new software needed?
– what is the most effective tool for Statistical Analysis Business Analytics and Business Intelligence?
– How likely is the current Prescriptive Analytics plan to come in on schedule or on budget?
– What is the difference between business intelligence business analytics and data mining?
– Is there a mechanism to leverage information for business analytics and optimization?
– What is the difference between business intelligence and business analytics?
– what is the difference between Data analytics and Business Analytics If Any?
– How do you pick an appropriate ETL tool or business analytics tool?
– What are the trends shaping the future of business analytics?
– What is our Prescriptive Analytics Strategy?
Business intelligence Critical Criteria:
Pay attention to Business intelligence management and explore and align the progress in Business intelligence.
– Research reveals that more than half of business intelligence projects hit a low degree of acceptance or fail. What factors influence the implementation negative or positive?
– What information can be provided in regards to a sites usage and business intelligence usage within the intranet environment?
– Can you easily add users and features to quickly scale and customize to your organizations specific needs?
– What does a typical data warehouse and business intelligence organizational structure look like?
– What is the difference between Enterprise Information Management and Data Warehousing?
– Is business intelligence set to play a key role in the future of Human Resources?
– What are the best BI and reporting tools for embedding in a SaaS application?
– What are the pros and cons of outsourcing Business Intelligence?
– What type and complexity of system administration roles?
– How do we use AI algorithms in practical applications?
– What are the best client side analytics tools today?
– Will your product work from a mobile device?
– How is Business Intelligence related to CRM?
– Can your product map ad-hoc query results?
– Do you offer formal user training?
– Does your system provide apis?
– How are you going to manage?
– Why BI?
Business operations Critical Criteria:
Interpolate Business operations planning and diversify disclosure of information – dealing with confidential Business operations information.
– What are the success criteria that will indicate that Prescriptive Analytics objectives have been met and the benefits delivered?
– Is legal review performed on all intellectual property utilized in the course of your business operations?
– How to move the data in legacy systems to the cloud environment without interrupting business operations?
– What vendors make products that address the Prescriptive Analytics needs?
– Are there Prescriptive Analytics Models?
Business process Critical Criteria:
Audit Business process failures and create Business process explanations for all managers.
– Do we identify maximum allowable downtime for critical business functions, acceptable levels of data loss and backlogged transactions, RTOs, RPOs, recovery of the critical path (i.e., business processes or systems that should receive the highest priority), and the costs associated with downtime? Are the approved thresholds appropriate?
– Have the segments, goals and performance objectives been translated into an actionable and realistic target business and information architecture expressed within business functions, business processes, and information requirements?
– Have senior executives clearly identified and explained concerns regarding Customer Service issues and other change drivers, and emphasized that major improvements are imperative?
– To what extent will this product open up for subsequent add-on products, e.g. business process outsourcing services built on top of a program-as-a-service offering?
– What is the importance of knowing the key performance indicators KPIs for a business process when trying to implement a business intelligence system?
– When conducting a business process reengineering study, what should we look for when trying to identify business processes to change?
– What are the disruptive Prescriptive Analytics technologies that enable our organization to radically change our business processes?
– Do you design data protection and privacy requirements into the development of your business processes and new systems?
– Do the functional areas need business process integration (e.g., order entl. billing, or Customer Service)?
– If we accept wire transfers what is the desired business process around supporting wire transfers?
– How do clients contact client services with any questions about business processes?
– How do you inventory and assess business processes as part of an ERP evaluation?
– Will existing staff require re-training, for example, to learn new business processes?
– Do changes in business processes fall under the scope of change management?
– What business process supports the entry and validation of the data?
– What is the business process?
Computational model Critical Criteria:
Detail Computational model risks and revise understanding of Computational model architectures.
– A compounding model resolution with available relevant data can often provide insight towards a solution methodology; which Prescriptive Analytics models, tools and techniques are necessary?
– Think of your Prescriptive Analytics project. what are the main functions?
– What are the short and long-term Prescriptive Analytics goals?
Computational science Critical Criteria:
Focus on Computational science projects and adopt an insight outlook.
– Which customers cant participate in our Prescriptive Analytics domain because they lack skills, wealth, or convenient access to existing solutions?
– How do senior leaders actions reflect a commitment to the organizations Prescriptive Analytics values?
– How important is Prescriptive Analytics to the user organizations mission?
Data mining Critical Criteria:
Weigh in on Data mining management and get going.
– Are there any easy-to-implement alternatives to Prescriptive Analytics? Sometimes other solutions are available that do not require the cost implications of a full-blown project?
– Do you see the need to clarify copyright aspects of the data-driven innovation (e.g. with respect to technologies such as text and data mining)?
– What types of transactional activities and data mining are being used and where do we see the greatest potential benefits?
– What is the difference between Data Analytics Data Analysis Data Mining and Data Science?
– How do we know that any Prescriptive Analytics analysis is complete and comprehensive?
– How do we Improve Prescriptive Analytics service perception, and satisfaction?
– What programs do we have to teach data mining?
Decision Engineering Critical Criteria:
Look at Decision Engineering tasks and gather practices for scaling Decision Engineering.
– What are your current levels and trends in key measures or indicators of Prescriptive Analytics product and process performance that are important to and directly serve your customers? how do these results compare with the performance of your competitors and other organizations with similar offerings?
– Do Prescriptive Analytics rules make a reasonable demand on a users capabilities?
– Are there recognized Prescriptive Analytics problems?
Decision Management Critical Criteria:
Infer Decision Management failures and create Decision Management explanations for all managers.
– Does Prescriptive Analytics appropriately measure and monitor risk?
– How will you measure your Prescriptive Analytics effectiveness?
Health, Safety and Environment Critical Criteria:
Scan Health, Safety and Environment results and get going.
– What are your results for key measures or indicators of the accomplishment of your Prescriptive Analytics strategy and action plans, including building and strengthening core competencies?
– Is maximizing Prescriptive Analytics protection the same as minimizing Prescriptive Analytics loss?
Health care in the United States Critical Criteria:
Start Health care in the United States projects and finalize the present value of growth of Health care in the United States.
– Do those selected for the Prescriptive Analytics team have a good general understanding of what Prescriptive Analytics is all about?
– Do we all define Prescriptive Analytics in the same way?
Health care provider Critical Criteria:
Define Health care provider planning and gather practices for scaling Health care provider.
– How do we maintain Prescriptive Analyticss Integrity?
– Are there Prescriptive Analytics problems defined?
Map reduce Critical Criteria:
Accommodate Map reduce leadership and interpret which customers can’t participate in Map reduce because they lack skills.
– Where do ideas that reach policy makers and planners as proposals for Prescriptive Analytics strengthening and reform actually originate?
– Who will be responsible for deciding whether Prescriptive Analytics goes ahead or not after the initial investigations?
Mathematical model Critical Criteria:
Use past Mathematical model results and work towards be a leading Mathematical model expert.
– Well-defined, appropriate concepts of the technology are in widespread use, the technology may have been in use for many years, a formal mathematical model is defined, etc.)?
– How does the organization define, manage, and improve its Prescriptive Analytics processes?
– Do we have past Prescriptive Analytics Successes?
Mathematical sciences Critical Criteria:
Match Mathematical sciences failures and raise human resource and employment practices for Mathematical sciences.
– Does Prescriptive Analytics analysis isolate the fundamental causes of problems?
– What are the business goals Prescriptive Analytics is aiming to achieve?
– How do we go about Securing Prescriptive Analytics?
Natural gas prices Critical Criteria:
Familiarize yourself with Natural gas prices failures and forecast involvement of future Natural gas prices projects in development.
– What management system can we use to leverage the Prescriptive Analytics experience, ideas, and concerns of the people closest to the work to be done?
– What are our needs in relation to Prescriptive Analytics skills, labor, equipment, and markets?
– Which individuals, teams or departments will be involved in Prescriptive Analytics?
Operations research Critical Criteria:
Collaborate on Operations research issues and customize techniques for implementing Operations research controls.
– What will be the consequences to the business (financial, reputation etc) if Prescriptive Analytics does not go ahead or fails to deliver the objectives?
– What is the total cost related to deploying Prescriptive Analytics, including any consulting or professional services?
Predictive analytics Critical Criteria:
Look at Predictive analytics outcomes and plan concise Predictive analytics education.
– Consider your own Prescriptive Analytics project. what types of organizational problems do you think might be causing or affecting your problem, based on the work done so far?
– What are direct examples that show predictive analytics to be highly reliable?
Structured data Critical Criteria:
Demonstrate Structured data governance and simulate teachings and consultations on quality process improvement of Structured data.
– What tools do you consider particularly important to handle unstructured data expressed in (a) natural language(s)?
– Does your organization have the right tools to handle unstructured data expressed in (a) natural language(s)?
– Meeting the challenge: are missed Prescriptive Analytics opportunities costing us money?
– Should you use a hierarchy or would a more structured database-model work best?
Unstructured data Critical Criteria:
Air ideas re Unstructured data adoptions and innovate what needs to be done with Unstructured data.
– How can you measure Prescriptive Analytics in a systematic way?
– Are we Assessing Prescriptive Analytics and Risk?
Utility companies Critical Criteria:
Extrapolate Utility companies results and adjust implementation of Utility companies.
– What potential environmental factors impact the Prescriptive Analytics effort?
– Have you identified your Prescriptive Analytics key performance indicators?
This quick readiness checklist is a selected resource to help you move forward. Learn more about how to achieve comprehensive insights with the Prescriptive Analytics Self Assessment:
Author: Gerard Blokdijk
CEO at The Art of Service | http://theartofservice.com
Gerard is the CEO at The Art of Service. He has been providing information technology insights, talks, tools and products to organizations in a wide range of industries for over 25 years. Gerard is a widely recognized and respected information expert. Gerard founded The Art of Service consulting business in 2000. Gerard has authored numerous published books to date.
To address the criteria in this checklist, these selected resources are provided for sources of further research and information:
Prescriptive Analytics External links:
Healthcare Prescriptive Analytics – Cedar Gate …
Applied statistics External links:
Journal of Applied Statistics: Vol 45, No 3 – tandfonline.com
FAQ – Master of Applied Statistics
Applied statistics (Book, 1978) [WorldCat.org]
Big data External links:
Databricks – Making Big Data Simple
Business Intelligence and Big Data Analytics Software
Loudr: Big Data for Music Rights
Business analytics External links:
Business Analytics and Strategic Decisions | SVB
Business Analytics. Data Science. Data Management. – …
What is Business Analytics? Webopedia Definition
Business intelligence External links:
Mortgage Business Intelligence Software :: Motivity Solutions
Small Business Intelligence for All | SizeUp
Business operations External links:
U.S. Forest Service – Business Operations
UofL Business Operations
HUB Business Operations Jobs
Business process External links:
Information technology and business process …
Infosys BPM – Business Process Management | BPM …
Computational model External links:
A Computational Model of Music Composition – DASH …
Computational science External links:
Computational Science and Engineering Education
Welcome | School of Computational Science and …
Data mining External links:
UT Data Mining
Data Mining on the Florida Department of Corrections Website
What is Data Mining in Healthcare?
Decision Engineering External links:
Decision engineering – encyclopedia article – Citizendium
decisionz.com – Decision Engineering (NZ) Ltd, Rated …
Decision Management External links:
FICO® Decision Management Suite | FICO®
Decision Management Solutions | Sapiens DECISION
Health, Safety and Environment External links:
Health, Safety and Environment Policies – Manual
Health, Safety and Environment Policies
Health, Safety and Environment (HSE) Practices – Anadarko
Health care provider External links:
A community based health care provider – trhs.org
Map reduce External links:
Hadoop Map Reduce Development – Introduction – YouTube
MongoDB Map Reduce – tutorialspoint.com
Mathematical model External links:
Mathematical model predicts Bengals-Cardinals in …
LCA Mathematical Model | The Methodology Center
Mathematical Model Drawing – Roswell Independent …
Mathematical sciences External links:
Mathematical Sciences | University of Arkansas
Department of Mathematical Sciences – IPFW
Department of Mathematical Sciences | Kent State University
Natural gas prices External links:
Compare Natural Gas Prices and Cost in Pennsylvania: UGI
Natural Gas Prices | StateImpact Pennsylvania
Natural Gas Prices & Rate Plans – Gas South
Operations research External links:
Operations research (Book, 1974) [WorldCat.org]
Operations Research (O.R.), or operational research in the U.K, is a discipline that deals with the application of advanced analytical methods to help make better decisions.
Systems Engineering and Operations Research
Predictive analytics External links:
Predictive Analytics Software, Social Listening | NewBrand
Strategic Location Management & Predictive Analytics | …
Inventory Optimization for Retail | Predictive Analytics
Structured data External links:
Structured Data Testing Tool – Google
SEC.gov | What Is Structured Data?
Structured Data for Dummies – Search Engine Journal
Unstructured data External links:
What is unstructured data? – Definition from WhatIs.com
Utility companies External links:
Utility Companies – Miami-Dade County